Results 61 to 70 of about 16,939 (236)

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Text zoning for job advertisements with bidirectional LSTMs [PDF]

, 2018
We present an approach to text zoning for job advertisements with neural networks. Text zoning refers to segmenting texts into eight classes differing from each other regarding content. It aims at capturing text parts dedicated to particular subjects, e.g.
openaire   +2 more sources

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

Advanced Science, EarlyView.
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu, Da‐Wen Sun, QingYi Wei, Yibing Zhang, Jidong Tang, Hongbin Pu   +5 more
wiley   +1 more source

Word Sense Disambiguation using a Bidirectional LSTM

CoRR, 2016
In this paper we present a clean, yet effective, model for word sense disambiguation. Our approach leverage a bidirectional long short-term memory network which is shared between all words. This enables the model to share statistical strength and to scale well with vocabulary size.
Mikael Kågebäck, Hans Salomonsson
openaire   +3 more sources

SPEECH SEPARATION BY MODIFIED DEEP NON-LINEAR FILTERING MODEL

Електроніка та інформаційні технології
Background. Automatic Speech Recognition (ASR) systems in single-channel experimental setups perform poorly in real-world scenarios when several talkers are placed near a microphone.
Andrii Tsemko, Ivan Karbovnyk
doaj   +1 more source

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

Advanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou, Qihang Zhen, Zexin Lv, Xinyue Cui, Suhui Wang, Minghua Hou, Zhan Zhou, Xiaogen Zhou, Guijun Zhang   +8 more
wiley   +1 more source

Comparative Deep Learning Analysis: Unveiling the Power of LSTM, BiLSTM, GRU, and BiGRU for Agricultural Stock Price Forecasting on the Indonesian Stock Exchange

Jurnal Teknologi dan Sistem Informasi
This study aims to analyze the performance of deep learning algorithms in predicting agricultural sector stock prices on the Indonesia Stock Exchange (IDX) by comparing four models: Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Gated ...
Muhammad Fadhlurrahman, Armin Darmawan
doaj   +1 more source

A Review of Failure Modes and Safety Strategies of Lithium‐Ion Batteries from Materials to Systems

Advanced Science, EarlyView.
A cascade‐aware framework is presented for lithium‐ion battery safety, linking thermal runaway initiation, acceleration, runaway reaction, and propagation with material‐, cell/pack‐, and system‐level interventions. By integrating failure mechanisms, quantitative safety indicators, and staged interception strategies, this review highlights how safer ...
Jin Hyeok Yang, Jae Yoon Sung, Hyunji Kweon, Seohyun Kim, Byunghoon Kim, Jongsoon Kim, Junyoung Mun, Jung Ho Kim, Ki Jae Kim   +8 more
wiley   +1 more source

Automatic Bi-LSTM Architecture Search Using Bayesian Optimisation for Vehicle Activity Recognition

, 2023
This paper presents a novel method to find optimal Bidirectional Long-Short Term Memory Neural Network (Bi-LSTM) using Bayesian Optimisation method for vehicle trajectory classification.
AlZoubi, A., Radhakrishnan , R.
core   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source